import re, collections

def words(text): return re.findall('[a-z]+', text.lower()) 

def train(features):
    model = collections.defaultdict(lambda: 1)
    for f in features:
        model[f] += 1
    return model

NWORDS = train(words(file('big.txt').read()))

alphabet = 'abcdefghijklmnopqrstuvwxyz'

def edits1(word):
    splits     = [(word[:i], word[i:]) for i in range(len(word) + 1)]
    deletes    = [a + b[1:] for a, b in splits if b]
    transposes = [a + b[1] + b[0] + b[2:] for a, b in splits if len(b)>1]
    replaces   = [a + c + b[1:] for a, b in splits for c in alphabet if b]
    inserts    = [a + c + b     for a, b in splits for c in alphabet]
    return set(deletes + transposes + replaces + inserts)

def known_edits2(word):
    return set(e2 for e1 in edits1(word) for e2 in edits1(e1) if e2 in NWORDS)

def known(words): return set(w for w in words if w in NWORDS)

def correct(word):
    candidates = known([word]) or known(edits1(word)) or known_edits2(word) or [word]
    return max(candidates, key=NWORDS.get)


import httplib
import xml.dom.minidom

data = """
<spellrequest textalreadyclipped="0" ignoredups="0" ignoredigits="1" ignoreallcaps="1">
<text> %s </text>
</spellrequest>
"""

def spellCheck(word_to_spell):

    con = httplib.HTTPSConnection("www.google.com")
    con.request("POST", "/tbproxy/spell?lang=en", data % word_to_spell)
    response = con.getresponse()

    dom = xml.dom.minidom.parseString(response.read())
    dom_data = dom.getElementsByTagName('spellresult')[0]

    if dom_data.childNodes:
        for child_node in dom_data.childNodes:
            result = child_node.firstChild.data.split()
        for word in result:
            if word_to_spell.upper() == word.upper():
                return True;
        return False;
    else:
        return True;
    
